Glaucoma is the leading cause of irreversible blindness globally, with over three million affected individuals in this country and seventy millio worldwide. This eye disease is widely recognized as a major health and socio-economic burden as an estimated 45% of patients progress to demonstrable loss of vision and approximately 15% eventually lose sight in one eye. As a blinding illness that generates more than seven million physician visits per year in this country, an improved paradigm for disease management is urgently needed. The singular unmet need for improved clinical management of glaucoma patients is accurate and detailed information on the daily intraocular pressure fluctuations and trends for each affected individual. Such comprehensive, long-term IOP data is currently not available as IOP measurements are typically only obtained from each patient 2-3 times a year during clinic visits. There is significant interest in high quality, personalized IOP data sets andit is widely believed that such comprehensive data will help improve clinical decision-making and the optimization of medical and surgical management for glaucoma. In this application, we test the hypothesis that convenient, on-demand IOP measurements can be achieved simply using light as a sensing medium in combination with a nanophotonics sensor micro-implant. The detection principle is based on changes in the optical resonance signature of the 600 m implant device containing a Fabry-Perot microcavity, whose signal-to-noise ratio performance is enhanced by engineered nanodot patterns embedded on a deformable membrane. The near-infrared resonance signature of the sensor shifts predictably in response to changes in the ambient pressure or IOP. The research teams from Caltech and UCSF have worked closely together for the past three years and have obtained proof of concept for the fundamental sensing principle and IOP sensing using light in rabbits in vivo. By leveraging expertise in nanophotonics from Caltech and ophthalmic device development from UCSF, the research team proposes in the present application to further develop and refine the IOP sensor to meet key performance required of a clinically useful device. The successful implementation of this light-based IOP sensing technology will significantly enhance both the patient's access to convenient, on demand self-monitoring and the physician's ability to fully utilize personalized IOP profiles to more effectively tailor treatment for individuals afflicted with this debilitating ye disease.